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INFOGRAPHIC: Big Data Alchemy

This infographic is about how banks can maximize the value of their customer data using big data analytics. While the volume of data has been increasing in recent years, many banks have not been able
…

This infographic is about how banks can maximize the value of their customer data using big data analytics. While the volume of data has been increasing in recent years, many banks have not been able to profit from this growth. Several challenges hold them back.

Transcript

1.
How can Banks Maximize the Value of
their Customer Data?
#digitaltransformation
of banking executives worldwide say
customer centricity is important
to them
But only
analyze customers’
share of wallet
of ﬁnancial institutions in
North America think that successful
big data initiatives will deﬁne
the winners in the future
However, only
Inﬂexible legacy systems A large European Bank embarked on a big data project
to analyze a large amount of unstructured data
Big data requires new
technologies and
processes to
An average company sees
a return of just
of bankers are cautious in
their use of big data due to
privacy issues
A recent security breach at a
leading UK-based bank exposed
databases of thousands of customer
ﬁles
Embed analytics into
core business processes
Strive towards full
executive sponsorship
for analytics initiatives
Develop and promote a
company-wide analytics
strategy
Establish a well-deﬁned
recruitment process to
attract analytics talent
Consolidate disparate analytics
teams into an Analytics Center
of Excellence
Set up strategic partnerships
for supplementary analytics skills
Build a robust data management
framework for the collection,
storage and use of structured
and unstructured data
Graduate to predictive and
prescriptive analytics that enable
more precise modeling of
customer behavior
Sources:
1. SAP and Bloomberg Businessweek Research Services, “Banks Betting Big on Big Data and Real-Time Customer Insight”, September 2013
2. Capgemini and EFMA, Retail Banking Voice of the Customer Survey, 2013
3. Microsoft and Celent, “How Big is Big Data: Big Data Usage and Attitudes among North American Financial Services Firms”, March 2013
4. Capgemini and the Economist Intelligence Unit, The Deciding Factor: Big Data and Decision-making, 2012
5. Computerworld UK, Deutsche Bank: Big data plans held back by legacy systems, February 2013
6. Finextra Research, Clear2Pay, NGDATA, “Monetizing Payments: Exploiting Mobile Wallets and Big Data”, 2013
7. Wikibon, “Enterprises Struggling to Derive Maximum Value from Big Data”, September 2013
8. Mail Online, “Exposed: Barclays account details for sale as 'gold mine' of up to 27,000 ﬁles is leaked in worst breach of bank data EVER”,
February 2014
of banks have
hands-on experience
with live big data
implementations
3/4 of banks do not have the right
resources to gain value from big data
Banks face the challenge of training
end-users of big data, who may not
be data experts themselves
How can Banks Scale-up to the
Next Level of Customer Data Analytics?
70% 29%
90% 37%
Silos of Data Block a Single Customer View
The Skills and Development Gap Needs Closing
Lack of Strategic Focus: Big Data Viewed as Just Another ‘IT Project’
Privacy Concerns Limit the Adoption of Customer Data Analytics
Reach out: Interested in reading the full report?
Head to http://www.capgemini-consulting.com/Big-Data-Customer-Analytics-in-Banks
Follow us on Twitter @capgeminiconsul or email dtri.in@capgemini.com
Faced difﬁculties in
and their integration with
big data systems
the extraction of data
from legacy systems
Impede data integration
Prevent a single
view of the customer
STORE ORGANIZE RETRIEVE
55 cents
on every dollar that it spends on big data
large volumes of
structured and
unstructured data
Such incidents reinforce
concerns about data privacy
62%
Drive a Shift from a ‘Data as an IT-asset’ to a
Establish a Strong Data Management Framework for Big Data
Develop Analytics Talent with a Targeted Recruitment and Continual Training Programs
‘Data as a Key Asset for Decision-Making’ Culture
Banks have not fully exploited customer data
Why are Banks Unable to Exploit Big Data?
th
Big Data Alchemy